Microglial Activation Correlates with Disease Progression and Upper Motor Neuron Clinical Symptoms in Amyotrophic Lateral Sclerosis

We evaluated clinicopathological correlates of upper motor neuron (UMN) damage in amyotrophic lateral sclerosis (ALS), and analyzed if the presence of the C9ORF72 repeat expansion was associated with alterations in microglial inflammatory activity.Microglial pathology was assessed by IHC with 2 different antibodies (CD68, Iba1), myelin loss by Kluver-Barrera staining and myelin basic protein (MBP) IHC, and axonal loss by neurofilament protein (TA51) IHC, performed on 59 autopsy cases of ALS including 9 cases with C9ORF72 repeat expansion.Microglial pathology as depicted by CD68 and Iba1 was significantly more extensive in the corticospinal tract (CST) of ALS cases with a rapid progression of disease. Cases with C9ORF72 repeat expansion showed more extensive microglial pathology in the medulla and motor cortex which persisted after adjusting for disease duration in a logistic regression model. Higher scores on the clinical UMN scale correlated with increasing microglial pathology in the cervical CST. TDP-43 pathology was more extensive in the motor cortex of cases with rapid progression of disease.This study demonstrates that microglial pathology in the CST of ALS correlates with disease progression and is linked to severity of UMN deficits

Milder Alzheimer\u27s Disease Pathology in Heart Failure and Atrial Fibrillation

Introduction:Heart failure (HF) and atrial fibrillation (AF) have been associated with a higher risk of Alzheimer’s disease (AD). Whether HF and AF are related to AD by enhancing AD neuropathological changes is unknown. Methods:We applied network analyses and multiple logistic regression models to assess the association between HF and AF with severity of AD neuropathology in patients from the National Alzheimer’s Coordinating Center database with primary neuropathological diagnosis of AD. Results:We included 1593 patients, of whom 129 had HF and 250 had AF. HF and AF patients were older and had milder AD pathology. In the network analyses, HF and AF were associated with milder AD neuropathology. In the regression analyses, age (odds ratio [OR] 0.94, 95

Correction: Clinical outcome measures in dementia with Lewy bodies trials: critique and recommendations.

The selection of appropriate outcome measures is fundamental to the design of any successful clinical trial. Although dementia with Lewy bodies (DLB) is one of the most common neurodegenerative conditions, assessment of therapeutic benefit in clinical trials often relies on tools developed for other conditions, such as Alzheimer's or Parkinson's disease. These may not be sufficiently valid or sensitive to treatment changes in DLB, decreasing their utility. In this review, we discuss the limitations and strengths of selected available tools used to measure DLB-associated outcomes in clinical trials and highlight the potential roles for more specific objective measures. We emphasize that the existing outcome measures require validation in the DLB population and that DLB-specific outcomes need to be developed. Finally, we highlight how the selection of outcome measures may vary between symptomatic and disease-modifying therapy trials

Clinical outcome measures in dementia with Lewy bodies trials: critique and recommendations

The selection of appropriate outcome measures is fundamental to the design of any successful clinical trial. Although dementia with Lewy bodies (DLB) is one of the most common neurodegenerative conditions, assessment of therapeutic benefit in clinical trials often relies on tools developed for other conditions, such as Alzheimer's or Parkinson's disease. These may not be sufficiently valid or sensitive to treatment changes in DLB, decreasing their utility. In this review, we discuss the limitations and strengths of selected available tools used to measure DLB-associated outcomes in clinical trials and highlight the potential roles for more specific objective measures. We emphasize that the existing outcome measures require validation in the DLB population and that DLB-specific outcomes need to be developed. Finally, we highlight how the selection of outcome measures may vary between symptomatic and disease-modifying therapy trials

Clinical outcome measures in dementia with Lewy bodies trials: critique and recommendations.

The selection of appropriate outcome measures is fundamental to the design of any successful clinical trial. Although dementia with Lewy bodies (DLB) is one of the most common neurodegenerative conditions, assessment of therapeutic benefit in clinical trials often relies on tools developed for other conditions, such as Alzheimer's or Parkinson's disease. These may not be sufficiently valid or sensitive to treatment changes in DLB, decreasing their utility. In this review, we discuss the limitations and strengths of selected available tools used to measure DLB-associated outcomes in clinical trials and highlight the potential roles for more specific objective measures. We emphasize that the existing outcome measures require validation in the DLB population and that DLB-specific outcomes need to be developed. Finally, we highlight how the selection of outcome measures may vary between symptomatic and disease-modifying therapy trials

Neuropathological consensus criteria for the evaluation of Lewy pathology in post-mortem brains: a multi-centre study

Currently, the neuropathological diagnosis of Lewy body disease (LBD) may be stated according to several staging systems, which include the Braak Lewy body stages (Braak), the consensus criteria by McKeith and colleagues (McKeith), the modified McKeith system by Leverenz and colleagues (Leverenz), and the Unified Staging System by Beach and colleagues (Beach). All of these systems use semi-quantitative scoring (4- or 5-tier scales) of Lewy pathology (LP; i.e., Lewy bodies and Lewy neurites) in defined cortical and subcortical areas. While these systems are widely used, some suffer from low inter-rater reliability and/or an inability to unequivocally classify all cases with LP. To address these limitations, we devised a new system, the LP consensus criteria (LPC), which is based on the McKeith system, but applies a dichotomous approach for the scoring of LP (i.e., “absent” vs. “present”) and includes amygdala-predominant and olfactory-only stages. α-Synuclein-stained slides from brainstem, limbic system, neocortex, and olfactory bulb from a total of 34 cases with LP provided by the Newcastle Brain Tissue Resource (NBTR) and the University of Pennsylvania brain bank (UPBB) were scanned and assessed by 16 raters, who provided diagnostic categories for each case according to Braak, McKeith, Leverenz, Beach, and LPC systems. In addition, using LP scores available from neuropathological reports of LP cases from UPBB (n = 202) and NBTR (n = 134), JT (UPBB) and JA (NBTR) assigned categories according to all staging systems to these cases. McKeith, Leverenz, and LPC systems reached good (Krippendorff’s α ≈ 0.6), while both Braak and Beach systems had lower (Krippendorff’s α ≈ 0.4) inter-rater reliability, respectively. Using the LPC system, all cases could be unequivocally classified by the majority of raters, which was also seen for 97.1% when the Beach system was used. However, a considerable proportion of cases could not be classified when using Leverenz (11.8%), McKeith (26.5%), or Braak (29.4%) systems. The category of neocortical LP according to the LPC system was associated with a 5.9 OR (p < 0.0001) of dementia in the 134 NBTR cases and a 3.14 OR (p = 0.0001) in the 202 UPBB cases. We established that the LPC system has good reproducibility and allows classification of all cases into distinct categories. We expect that it will be reliable and useful in routine diagnostic practice and, therefore, suggest that it should be the standard future approach for the basic post-mortem evaluation of LP

The Alzheimer's Disease Neuroimaging Initiative 2 Biomarker Core: A review of progress and plans

INTRODUCTION: We describe Alzheimer's Disease Neuroimaging Initiative (ADNI) Biomarker Core progress including: the Biobank; cerebrospinal fluid (CSF) amyloid beta (Aβ1-42), t-tau, and p-tau181 analytical performance, definition of Alzheimer's disease (AD) profile for plaque, and tangle burden detection and increased risk for progression to AD; AD disease heterogeneity; progress in standardization; and new studies using ADNI biofluids. METHODS: Review publications authored or coauthored by ADNI Biomarker core faculty and selected non-ADNI studies to deepen the understanding and interpretation of CSF Aβ1-42, t-tau, and p-tau181 data. RESULTS: CSF AD biomarker measurements with the qualified AlzBio3 immunoassay detects neuropathologic AD hallmarks in preclinical and prodromal disease stages, based on CSF studies in non-ADNI living subjects followed by the autopsy confirmation of AD. Collaboration across ADNI cores generated the temporal ordering model of AD biomarkers varying across individuals because of genetic/environmental factors that increase/decrease resilience to AD pathologies. DISCUSSION: Further studies will refine this model and enable the use of biomarkers studied in ADNI clinically and in disease-modifying therapeutic trials

Alzheimer's disease cerebrospinal fluid biomarker in cognitively normal subjects

In a large multicentre study, Toledo et al. examine core Alzheimer's disease CSF biomarkers in 1233 cognitively normal subjects aged 40-85 years. Alzheimer disease-like changes in Aβ1-42 are seen as early as middle age, while APOE genotype strongly modifies age-related effects on both Aβ1-42 and phosphorylated/total ta

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Dementia with Lewy bodies: Impact of co-pathologies and implications for clinical trial design

Dementia with Lewy bodies (DLB) is clinically defined by the presence of visual hallucinations, fluctuations, rapid eye movement (REM) sleep behavioral disorder, and parkinsonism. Neuropathologically, it is characterized by the presence of Lewy pathology. However, neuropathological studies have demonstrated the high prevalence of coexistent Alzheimer's disease, TAR DNA-binding protein 43 (TDP-43), and cerebrovascular pathologic cases. Due to their high prevalence and clinical impact on DLB individuals, clinical trials should account for these co-pathologies in their design and selection and the interpretation of biomarkers values and outcomes. Here we discuss the frequency of the different co-pathologies in DLB and their cross-sectional and longitudinal clinical impact. We then evaluate the utility and possible applications of disease-specific and disease-nonspecific biomarkers and how co-pathologies can impact these biomarkers. We propose a framework for integrating multi-modal biomarker fingerprints and step-wise selection and assessment of DLB individuals for clinical trials, monitoring target engagement, and interpreting outcomes in the setting of co-pathologies.Wellcome Clinical Research Career Development Fellowship. Grant Number: 205167/Z/16/Z; National Institute for Health Research (NIHR); National Institute of Neurological Disorders and Stroke. Grant Number: 1ZIANS003154; NIH. Grant Numbers: P30 AG62677, U01 NS100620, U19 AG 071754, U54 NS110435 NINDS. Grant Number: U01NA100610; National Institute on Aging. Grant Number: P30AG072959Peer reviewe